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Comparison of the Foveal Avascular Zone in Diabetic Retinopathy, High Myopia and Normal Fundus Images.

机译:糖尿病视网膜病变,高近视和正常眼睛图像中变形缺血区的比较。

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To quantitatively describe and evaluate a new image processing technique for estimating the Foveal Avascular Zone (FAZ) in subjects with Diabetic Retinopathy and myopes. From a total of 328 images obtained from Diabetic Retinopathy (113), myopes (120) and normal (93), the FAZ dimensions were quantified using a new image processing algorithm. These parameters were also determined manually and by the OCT manufacturer's inbuilt algorithm. In the new technique, the images were first pre-processed by using a DOG filter iteratively before being complemented followed by a Prewitt edge detection and repeated image dilation at angles of 0°, 45° and 90°. Image closure was then applied followed by noise and small object removal which resulted in the segmented boundary. For deeper insight into shape change, in addition to the diameter of the FAZ other parameters such as the area, diameter, major axis, minor axis, orientation, perimeter vessel avascular density (VAD), Vessel diameter Index (VDI), etc. were obtained. The circularity index was calculated using the FAZ area and perimeter parameters. The mean FAZ diameter (mm) by the new automated technique, manual-segmentation (ground truth), and inbuilt instrument algorithm were 0.67 ± 0.87, 0.67 ± 0.72 and 0.61 ± 0.14. The mean of FAZ area (mm2) was 0.36 ± 0.10, 0.33 ± 0.09 and 0.43 ± 0.14 in normal, myopia and diabetic subjects respectively. The new technique shows considerable improvement in accuracy (mean ± SD) when compared to the inbuilt system segmentation and the ground truth (manual marking by an expert clinician). The study results show that the FAZ area in Diabetic Retinopathy is significantly different (p=0.003) when compared to myopic eyes (p=0.016) and normals.
机译:为了定量描述和评估患有糖尿病视网膜病变和肌瘤的受试者中变形缺血区(FAZ)的新图像处理技术。从患有糖尿病视网膜病变(113),近视(120)和正常(93)的总共328个图像,使用新的图像处理算法量化FAZ尺寸。这些参数也是手动确定的,由OCT制造商的内置算法确定。在新技术中,首先通过使用狗滤波器进行预处理在互补后进行预处理,然后在0°,45°和90°的角度下重复图像扩张。然后应用图像封闭,然后应用噪声和小对象去除,从而导致分段边界。为了更深入地了解形状变化,除了FAZ其他参数的直径之外,诸如面积,直径,长轴,短轴,方向,周边血管缺血密度(VAD),容器直径指数(VDI)等获得。使用FAZ区域和周边参数计算圆形指数。通过新的自动化技术,手动分割(地基)和内置仪器算法的平均FAZ直径(mm)为0.67±0.87,0.67±0.72和0.61±0.14。 F形(MM2)的平均值分别为正常,近视和糖尿病受试者的0.36±0.10,0.33±0.09和0.43±0.14。与内置系统分割和地面真理相比(专家临床医生的手动标记)相比,新技术表现出准确性(平均值±SD)的显着提高。研究结果表明,与近视眼(P = 0.016)和法线相比,糖尿病视网膜病变中的FAZ区域显着不同(p = 0.003)。

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